By Aaron Schilke, Vice President of Enterprise at Zendesk
It would be fair to say that the manufacturing industry is rapidly moving towards digital transformation. The pandemic exposed how fragile our global supply chains are, resulting in shortages of shelves and overstock in warehouses. Meanwhile, as the pandemic subsides, inflation is driving up the cost of goods and logistics, putting pressure on companies that have been recovering since the past few years. It’s no surprise that manufacturers are looking for ways to cut costs while maintaining quality.
Artificial Intelligence (AI) Can unlock savings and create better CX. Here are 4 ways manufacturers are using AI in customer support and seeing big results.
1: Implementing intelligent bots
AI bots Quickly assist customers 24/7 by answering low-value customer questions like where the order is and expected delivery date, or by bringing up relevant product documentation the customer has questions about. The bots are also capable of collecting information from customers, if necessary, for agent augmentation.
According to Zendesk’s CX Trends research, 60% of manufacturers say that intelligent bots help reduce the amount of interaction with customers by focusing on simple questions. What’s more, 66% agree that AI/bots have led to huge cost savings over the past year.
impossible foods is a manufacturer best known for its Impossible Burger. When a new partnership with Burger King introduced the Impossible Whopper and brought in a landslide of new customer communications, the company used AI-powered bots for faster support.
“We needed to step back and figure out how we could grow our team,” said Gabriel McCobbin, Senior Manager of Customer Advocacy at Impossible Foods. Result? 50% of ticket volume was removed through the help center, ticket forms, and bots.
2: Remote Troubleshooting
When something breaks, customers want someone to help them solve their problem. In the old days, this would essentially mean that a technician is dispatched to fix things on site. But now, AI can often troubleshoot without the need for human intervention. When your data, systems and corrective actions are all documented and connected, machine learning can offer quick solutions to common problems.
Customers are eager for this kind of intelligent service. zendesk research Shows that 69% of consumers feel that service agents should have the ability to help resolve problems remotely, and 61% of manufacturing leaders say that virtual tools result in a reduction in the number of in-home repair visits Has come
AI can also be useful on the production line before work begins. Manufacturers are using AI to train robots in pre-production and fine-tune them for improved speed, accuracy and efficiency. But IoT connectivity is useful beyond smart factories. Surfacing your customers’ IoT connected device data into one integrated workspace Shows your agents what the customer has already tried when remote troubleshooting requires a human.
3: Self Service Automation
With the focus on factory efficiency, it can be easy to overlook the customer experience. Many manufacturers still manually process new orders or customer claims. Some people are even using old fashioned ledgers or spreadsheets on the desktop – and this inhibits automation and increases the risk of errors. When a customer inquires about an order, the support agents have a hard time getting the details they need. These manual processes mean that orders and claims can be missed by mistake because the data is not connected. Furthermore, it makes self-service nearly impossible – without connected data, customers can’t find their own answers. It is a frustrating experience for all.
Offering an AI-powered self-service portal for customers eliminates a lot of such manual work, thereby increasing efficiency and customer satisfaction. A simple form submission can collect all the necessary information, including uploaded photos, to automatically start the backend ordering or claims process. Self-service portals can also give customers an easy place to get answers to common questions without the need for human intervention. This efficiency is critical for manufacturers looking to grow their CX operations to drive loyalty and long-term growth.
4: AI-Powered Knowledge Management
Customer-facing teams spend an inordinate amount of time sorting through thousands of product documents to find the right information on parts and machines. This is true for back-office agents answering email and service technicians in the field. Outdated processes lead to long wait times for customers who can’t wait, and are willing to walk away after a bad experience with your company.
A knowledge management system can turn your most frequently used product documents into one Help Center Articles that empower customers to troubleshoot on their own. It saves everyone time, and as the saying goes, time is money.
Ingersoll Rand Overhauled its support processes and implemented a searchable knowledge base to better serve customers. This was especially important, as the manufacturer builds its products to last—Ingersoll Rand still serves some products that are 50 years old.
“We didn’t have a central repository where everything was kept. You’d go into a filing cabinet and pull out this little microfiche, and read or print it,” says Kelly Dees, vice president of Global Customer Experience at Ingersoll Rand. Needless to say, this became a resource drain and created a backlog on service requests. The company implemented an AI-powered help center with a library of searchable digital manuals. so that customers can help themselves. It also gives agents relevant information about customers in case they need to contact for assistance.
build better relationships
Creating top-notch customer service can be a challenge when the budget is tight. The good news is that there are intelligent solutions available today. Manufacturers have the ability to shape the future through data – optimizing operations, creating innovative products and improving customer experience. Deploying AI-powered tools can supercharge your CX without adding excessive complexity or overhead.
The views and opinions expressed here are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
